All known methods of reduction of high frequency random noise in images reduce to replacement of initial pixel value by some average value over some area near the initial pixel. They differ mainly in the choice of filters, that is in the choice of the weights, with which the pixel values are summed during averaging and in the choice of the summation algorithms saving computing time. The summation algorithms may involve Fourier transformations, but the principle remains the same.
These methods do not distinguish the noise from the useful high-frequency components of the true image and as a consequence they reduce both to the same extent. The noise reduction smears an image, and the fine details of the image, if they were obscured by the noise, become even less visible after the noise reduction. The smearing is an unavoidable consequence of noise reduction, if no additional information about the noise or the image structure is available.